The approaches described in this section are approaches that could be pursued, but not necessarily approaches that have been previously conceived or pursued. Therefore, unless otherwise indicated, it should not be assumed that any of the approaches described in this section qualify as prior art merely by virtue of their inclusion in this section.
Large business-critical applications are complex and experience highly varying load and usage patterns. These applications are expected to provide certain service guarantees in terms of response time, throughput, uptime, and availability. At times, it may be desirable to change a system that includes such applications. Such a change might involve upgrading the system's database or modifying a configuration, for example. However, before any change is made to a production system, extensive testing and validation should be performed in a test system. In order to be confident that a change will not cause problems (e.g., errors or performance issues) in the production system once that change is introduced into the production system, a system tester should try to expose the test system to a workload that is very similar to the workload that the production system would actually experience in a real world environment.
Previous testing approaches have been inadequate because none of these previous testing approaches has been able to replicate a real production workload in a test system. According to one approach, a set of test scripts is written to test commonly executed code paths. Although this approach can be useful for performing regression testing and functional testing, this approach does not mimic a production workload. This approach usually stresses the testing system only to a very minimal extent.
Under another approach, human users are asked to use the test system as though the test system were a production system. However, this approach is very random and non-deterministic. This approach often fails to reproduce the load patterns that would be experienced in an actual production environment.
What is needed is a technique that exposes a testing system to the same workload to which the production system actually would be exposed.